Disruptive innovation: No better time
In the late 1990s, Clayton Christensen coined the term “disruptive innovation.” It was heralded as a way to smash through the tendency for slow, incremental, and supposedly “safe” change. In the decades that followed, companies such as Facebook, Amazon, Apple, Netflix, and Google, collectively referred to as the FAANGs, produced innovations that disrupted entire economic sectors, from news, book, and music publishing to brick-and-mortar retail. Even relatively young industries such as computers and telecommunications were upended practically overnight by integrating voice, video, text, and graphics into a single handheld device. It has certainly paid off. The five FAANGs alone now have a combined market capitalization approaching $5 trillion. That was innovation causing disruption.
In recent months, we’ve witnessed a completely different type of situation. The world has been turned upside down by the combined effects of a dangerous virus, a brutal murder, and the actions and non-actions taken by governments and other organizations in response—all of which have been greatly amplified by the very technologies made ubiquitous by the FAANGs. The huge difference is that instead of innovation causing the disruption, the disruption came first, forcing organizations to either innovate or die.
With this in mind, let’s take a look at three foundational areas undergoing massive disruption and how KM can play a role in driving change through innovation— and not just technological innovation, but people and process innovation as well. The three areas are how we live, how we work, and how we learn.
Changing how we live
The disruption: Much of the current disruption comes from the many restrictions suddenly imposed on everyday activities we used to take for granted. Sessions with a doctor, dentist, hair stylist, altered. How we purchase almost everything, from groceries to medicine to travel and entertainment, has moved online. All of this has accelerated the trend toward increased automation, enabled by AI and machine learning. It’s hard to escape. You’ve seen those annoying screen. They often can’t even answer the simplest questions. It seems AI isn’t so intelligent after all.
The KM innovation opportunity: The upshot is we need human intelligence now more than ever. Machines do what they’re taught. And when they’re taught to learn on their own they can, and sometimes do, “go rogue,” which is why we need to build reliable governance models to properly maintain the growing storehouses of knowledge being applied automatically at high volume and high speed. Which leads us to…
Changing how we work
The disruption: What we used to call a “job” is yet another hallowed tradition undergoing disruption. We can no longer count on the existence of a stable workforce, either on the supply or the demand side. With the push to move more functions online, disruptive technologies such as robotic process automation are rendering old skill sets obsolete, while at the same time creating the need for new ones.
The KM innovation opportunity: Moving everything we do to an online environment would be a serious mistake. Physical presence still has a critical role, especially where the exchange of knowledge is concerned. Computer screens are flat, almost lifeless. You miss many of the subtleties that come with physical presence— the sights, the sounds, the smells, the atmosphere—all of which send weak signals that stimulate thoughts, questions, and ideas. We need to find innovative ways of blending physical and virtual proximity. A good place to start is by creating a more enriched user experience. Dust off those old augmented/virtual reality ideas and start finding innovative ways to make them real so we don’t miss out on those non-verbal signals that can make all the difference, especially when critical decisions are being made.
And speaking of collaboration, as a knowledge manager/practitioner/leader, you should look for ways to promote not only collaboration among people, but among people and machines. Encourage your people to focus on doing what humans do best: questioning, anticipating, sense-making, problem-solving, integrating, and most importantly … innovating. Then help them learn how to use computers to provide the sophisticated processing and number-crunching needed to support their knowledge-intensive work. Aim to create a virtuous cycle in which humans teach machines and machines teach humans. Which brings us to…